class_docstr: Class for fitting the Free Water Tensor Model 
docstr: Given a free water tensor model fit, predict the signal on the
  vertices of a gradient table
  
  Parameters
  ----------
  gtab : a GradientTable class instance
      The gradient table for this prediction
  
  S0 : float array
     The mean non-diffusion weighted signal in each voxel. Default: 1 in
     all voxels.
  
  Returns
  -------
  S : (..., N) ndarray
      Simulated signal based on the free water DTI model
docstr_tok: ["Given","a","free","water","tensor","model","fit",",","predict","the","signal","on","the","vertices","of","a","gradient","table","Parameters","--","--","--","--","--","gtab",":","a","GradientTable","class","instance","The","gradient","table","for","this","prediction","S0",":","float","array","The","mean","non-diffusion","weighted","signal","in","each","voxel",".","Default",":","1","in","all","voxels",".","Returns","--","--","--","-","S",":","(","...",",","N",")","ndarray","Simulated","signal","based","on","the","free","water","DTI","model"]
code: def predict(self, gtab, S0=1):
      r"""Given a free water tensor model fit, predict the signal on the
      vertices of a gradient table
  
      Parameters
      ----------
      gtab : a GradientTable class instance
          The gradient table for this prediction
  
      S0 : float array
         The mean non-diffusion weighted signal in each voxel. Default: 1 in
         all voxels.
  
      Returns
      -------
      S : (..., N) ndarray
          Simulated signal based on the free water DTI model
      """
      return fwdti_prediction(self.model_params, gtab, S0=S0)
  
imports: import warnings
  import numpy
  import scipy.optimize
  from dipy.reconst.base import ReconstModel
  from dipy.reconst.dti import TensorFit, design_matrix, decompose_tensor, _decompose_tensor_nan, from_lower_triangular, lower_triangular
  from dipy.reconst.dki import _positive_evals
  from dipy.reconst.vec_val_sum import vec_val_vect
  from dipy.core.ndindex import ndindex
  from dipy.core.gradients import check_multi_b
  from dipy.reconst.multi_voxel import multi_voxel_fit
label_desc: Use image node_id 3 for calling the FreeWaterTensorFit obj's underlying member method code with example usage: obj.predict(gtab, S0) and returns: fwdti_prediction